The BOOTSTRAPPING APPROACH for INFERRING CONFIDENT FREIGHT TRANSPORT MATRICES

Transport studies require, as a preliminary step, conducting a survey process to a sample of the universe of users of the transportation system. The statistical reliability of the data determines the goodness of the results and conclusions that can be inferred from the analyses and models generated. In this communication a methodology, based on the techniques of “bootstrapping”, to the robust statistical estimate of freight transport matrices is presented ; this allows to generate the confidence intervals of travel between origin-destination pairs defined by each cell of the origin-destination matrix derived from a freight transport survey. This result is of interest in defining the dimensions of certainty for matrix cells and subsequent adjustment by techniques based on aggregate data (i.e. traffic counts, cordon line matrices, paths, etc.). The techniques of “bootstrapping” originated in the 70’s, although widely used during the 90’s, have not been fully exploited in the field of freight transport studies. To address this study a data set from a statistically reliable freight transport study conducted in Spain at the level of multi-province regions has been used.